Purple Dot | 1x Senior Full Stack Engineer (London, UK) + 1x Customer Solutions Engineer (New York, US) | 2 days/week in office | Full-time
At Purple Dot, we are on a mission to create a world where, ultimately, every product that is manufactured is sold. The current e-commerce model leaves brands waiting for stock to arrive at the warehouse before they can start selling, leading to missed sales opportunities, unsold inventory and waste. We believe the next wave of innovation will happen in the time before stock arrives, enabling brands to sell inventory no matter where it is in the world. Our pre-commerce platform puts the power back in brands’ hands, allowing them to take control of their sales timelines and maximise revenue potential.
And we make pre-orders trust worthy for the shoppers too, keeping their money in escrow until items ship, and always up to date on where their pre-order is at, with an option to cancel no questions asked.
We've raised a $10m Series A in 2024, we've plenty of runway left and we're looking for help as we scale our platform through the next order of magnitude in terms of load on the system and ultimately the number of dollars we process.
We are a team of 22 split evenly between the UK and US. 32% female, including the CEO. All of us have a mix of startup and big tech experience. For the founding team this is our second (so far :) successful startup.
* customer solutions engineer - based in New York, US - to work with our support and sales teams to help make going live with and using Purple Dot a delightful experience for brands and their shoppers: https://purpledot.notion.site/customer-solutions-engineer-us... EDIT: WE'VE MADE THIS HIRE NOW
Like everything else we do, we interview fast, and you will deal with me (head of engineering) throughout.
Ditto on not being able to rely on some mechanical turk services - although the quality of answers/labels you get back inevitably depends on how well you have laid out the task at hand, we have additionally witnessed poor quality output that was outright rogue - tasks being completed in sub seconds or same answers given by a user no matter the question - both pointing to tasks being completed by bots not humans.
In fact we had resolved to building a turker bot detector and started rejecting tasks completed in suspicious ways. Only once we have built ourselves a trusted turkers population did we start to get quality data back. I suspect most people don't bother to go back and reject poor quality answers and that is why the bots survive.
Wow, I believe it. We didn't have so much a rogue situation, but you really do have to constrain their actions to just what you wanted. I tried to find the source but there was some YouTube video I watched where the guy made this good comment about creating GUIs where you have to put a real emphasis on preventing users from doing things you do not want them to do. You can't always focus on features but also constraints. I really took that message to heart after experiencing some of the human unpredictability found in building up training data. It made for some interesting payment debates to ask them to redo some work that was incomplete. Fun stuff.
We use a multitude of models - linear and non-linear, supervised and unsupervised - to surface the best user-generated content from social for our clients.
Our ML stack is written almost entirely in Python - because of the readily available excellent libraries that give you many of the tools you'll need in your ML toolbox (matplotlib, numpy, pandas, scikit-image, scikit-learn, scipy to mention just a few). We have some more sophisticated image processing in C++. We find ourselves attacking quite a number of machine learning problems so to make our workflow more efficient we have built a layer of functionality above these libraries to manage the flow of data and speed up model prototyping and assessment. Processing input data and model fitting is usually done locally, with any hyper-parameter grid search or other computationally intensive tasks being run on a remote, cloud hosted cluster spun up on-demand.
Our tech is built around lambda architecture principles - we have a live path that processes new social content to the extent required to make content immediately available to relevant clients, and a batch path that processes complete datasets daily. Our ML models get used on both paths.
With a neat set of Python libraries for data manipulation and model definitions and our own model prototyping and assessment rig the biggest challenge is always building big, quality datasets. This continues to be our biggest learning and we are always keen to explore how others tackle this. We rely on a combination of in-house turking (which we consider a vital model development stage), external turking services (for volume) and have additionally looked at some knowledge transfer techniques.
At Purple Dot, we are on a mission to create a world where, ultimately, every product that is manufactured is sold. The current e-commerce model leaves brands waiting for stock to arrive at the warehouse before they can start selling, leading to missed sales opportunities, unsold inventory and waste. We believe the next wave of innovation will happen in the time before stock arrives, enabling brands to sell inventory no matter where it is in the world. Our pre-commerce platform puts the power back in brands’ hands, allowing them to take control of their sales timelines and maximise revenue potential.
And we make pre-orders trust worthy for the shoppers too, keeping their money in escrow until items ship, and always up to date on where their pre-order is at, with an option to cancel no questions asked.
We've raised a $10m Series A in 2024, we've plenty of runway left and we're looking for help as we scale our platform through the next order of magnitude in terms of load on the system and ultimately the number of dollars we process.
We are a team of 22 split evenly between the UK and US. 32% female, including the CEO. All of us have a mix of startup and big tech experience. For the founding team this is our second (so far :) successful startup.
I have two engineering role open:
* senior full stack engineer - based in London, UK - to join our core engineering team of 6 that are shipping our product roadmap: https://purpledot.notion.site/senior-full-stack-engineer-uk EDIT: WE'VE MADE THIS HIRE NOW
* customer solutions engineer - based in New York, US - to work with our support and sales teams to help make going live with and using Purple Dot a delightful experience for brands and their shoppers: https://purpledot.notion.site/customer-solutions-engineer-us... EDIT: WE'VE MADE THIS HIRE NOW
Like everything else we do, we interview fast, and you will deal with me (head of engineering) throughout.
me: https://linkedin.com/in/rtkaleta